"Passive activity monitoring offers a potentially simple solution for assessing patients’ compliance with their home exercise prescriptions. Activity monitoring today, however, often relies on camera-based systems, including video and motion cameras [10,11] or lab-prototyped custom sensors [12-15]. In the area of camera-based activity detection, Cucciara and colleagues explored techniques for the automatic video extraction of moving objects and people , and Goffredo and colleagues explored techniques for evaluating balance strategies and postural sway . "
[Show abstract][Hide abstract] ABSTRACT: In the physical therapy setting, physical therapists (PTs) often prescribe exercises for their clients to perform at home. However, it is difficult for PTs to obtain information about their clients' compliance with the prescribed exercises, the quality of performance and symptom magnitude. We present an iPod-based system for capturing this information from individuals with vestibular hypofunction while they perform gaze stabilization exercises at home.
The system's accuracy for measurement of rotational velocity against an independent motion tracker was validated. Then a seven day in-home trial was conducted with 10 individuals to assess the feasibility of implementing the system. Compliance was measured by comparing the recorded frequency and duration of the exercises with the exercise prescription. The velocity and range of motion of head movements was recorded in the pitch and yaw planes. The system also recorded dizziness severity before and after each exercise was performed. Each patient was interviewed briefly after the trial to ascertain ease of use. In addition, an interview was performed with PTs in order to assess how the information would be utilized.
The correlation of the velocity measurements between the iPod-based system and the motion tracker was 0.99. Half of the subjects were under-compliant with the prescribed exercises. The average head velocity during performance was 140 deg/s in the yaw plane and 101 deg/s in the pitch plane.
The iPod-based system was able to be used in-home. Interviews with PTs suggest that the quantitative data from the system will be valuable for assisting PTs in understanding exercise performance of patients, documenting progress, making treatment decisions, and communicating patient status to other PTs.
Journal of NeuroEngineering and Rehabilitation 04/2014; 11(1):69. DOI:10.1186/1743-0003-11-69 · 2.74 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Since falls are a major public health problem among older people, the number of systems aimed at detecting them has increased dramatically over recent years. This work presents an extensive literature review of fall detection systems, including comparisons among various kinds of studies. It aims to serve as a reference for both clinicians and biomedical engineers planning or conducting field investigations. Challenges, issues and trends in fall detection have been identified after the reviewing work. The number of studies using context-aware techniques is still increasing but there is a new trend towards the integration of fall detection into smartphones as well as the use of machine learning methods in the detection algorithm. We have also identified challenges regarding performance under real-life conditions, usability, and user acceptance as well as issues related to power consumption, real-time operations, sensing limitations, privacy and record of real-life falls.
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